Relative Abundance Of Class Research Articles

Spatiotemporal dynamics of the resistome and virulome of riverine microbiomes disturbed by a mining mud tsunami

Aquatic ecosystems are highly vulnerable to anthropogenic activities. However, it remains unclear how the microbiome responds to press disturbance events in these ecosystems. We examined the impact of the world's largest mining disaster (Brazil, 2015) on sediment microbiomes in two disturbed rivers compared to an undisturbed river during 390 days post-disturbance. The diversity and structure of the virulome and microbiome, and of antibiotic and metal resistomes, consistently differed between the disturbed and undisturbed rivers, particularly at day 7 post-disturbance. 684 different ARGs were predicted, 38% were exclusive to the disturbed rivers. Critical antibiotic resistance genes (ARGs), e.g., mcr and ereA2, were significantly more common in the disturbed microbiomes. 401 different ARGs were associated with mobile genetic elements (MGEs), 95% occurred in the disturbed rivers. While plasmids were the most common MGEs with a broad spectrum of ARGs, spanning 16 antibiotic classes, integrative conjugative elements (ICEs) and integrons disseminated ARGs associated with aminoglycoside and tetracycline, and aminoglycoside and beta-lactam, respectively. A significant increase in the relative abundance of class 1 integrons, ICEs, and pathogens was identified at day 7 in the disturbed microbiomes, 72-, 14- and 3- fold higher, respectively, compared with the undisturbed river. Mobile ARGs associated with ESKAPEE group pathogens, while metal resistance genes and virulence factor genes in nonpathogenic hosts predominated in all microbiomes. Network analysis showed highly interconnected ARGs in the disturbed communities, including genes targeting antibiotics of last resort. Interactions between copper and beta-lactam/aminoglycoside/macrolide resistance genes, mostly mobile and critical, were also uncovered. We conclude that the mud tsunami resulted in resistome expansion, enrichment of pathogens, and increases in promiscuous and mobile ARGs. From a One Health perspective, mining companies need to move toward more environmentally friendly and socially responsible mining practices to reduce risks associated with pathogens and critical and mobile ARGs.

Metagenomic and Resistome Analysis of a Full-Scale Municipal Wastewater Treatment Plant in Singapore Containing Membrane Bioreactors.

Reclaimed water provides a water supply alternative to address problems of scarcity in urbanized cities with high living densities and limited natural water resources. In this study, wastewater metagenomes from 6 stages of a wastewater treatment plant (WWTP) integrating conventional and membrane bioreactor (MBR) treatment were evaluated for diversity of antibiotic resistance genes (ARGs) and bacteria, and relative abundance of class 1 integron integrases (intl1). ARGs confering resistance to 12 classes of antibiotics (ARG types) persisted through the treatment stages, which included genes that confer resistance to aminoglycoside [aadA, aph(6)-I, aph(3′)-I, aac(6′)-I, aac(6′)-II, ant(2″)-I], beta-lactams [class A, class C, class D beta-lactamases (blaOXA)], chloramphenicol (acetyltransferase, exporters, floR, cmIA), fosmidomycin (rosAB), macrolide-lincosamide-streptogramin (macAB, ereA, ermFB), multidrug resistance (subunits of transporters), polymyxin (arnA), quinolone (qnrS), rifamycin (arr), sulfonamide (sul1, sul2), and tetracycline (tetM, tetG, tetE, tet36, tet39, tetR, tet43, tetQ, tetX). Although the ARG subtypes in sludge and MBR effluents reduced in diversity relative to the influent, clinically relevant beta lactamases (i.e., blaKPC, blaOXA) were detected, casting light on other potential point sources of ARG dissemination within the wastewater treatment process. To gain a deeper insight into the types of bacteria that may survive the MBR removal process, genome bins were recovered from metagenomic data of MBR effluents. A total of 101 close to complete draft genomes were assembled and annotated to reveal a variety of bacteria bearing metal resistance genes and ARGs in the MBR effluent. Three bins in particular were affiliated to Mycobacterium smegmatis, Acinetobacter Iwoffii, and Flavobacterium psychrophila, and carried aquired ARGs aac(2′)-Ib, blaOXA−278, and tet36 respectively. In terms of indicator organisms, cumulative log removal values (LRV) of Escherichia coli, Enterococci, and P. aeruginosa from influent to conventional treated effluent was lower (0–2.4), compared to MBR effluent (5.3–7.4). We conclude that MBR is an effective treatment method for reducing fecal indicators and ARGs; however, incomplete removal of P. aeruginosa in MBR treated effluents (<8 MPN/100 mL) and the presence of ARGs and intl1 underscores the need to establish if further treatment should be applied prior to reuse.

Increasing the Accuracy of Crowdsourced Information on Land Cover via a Voting Procedure Weighted by Information Inferred from the Contributed Data

Simple consensus methods are often used in crowdsourcing studies to label cases when data are provided by multiple contributors. A basic majority vote rule is often used. This approach weights the contributions from each contributor equally but the contributors may vary in the accuracy with which they can label cases. Here, the potential to increase the accuracy of crowdsourced data on land cover identified from satellite remote sensor images through the use of weighted voting strategies is explored. Critically, the information used to weight contributions based on the accuracy with which a contributor labels cases of a class and the relative abundance of class are inferred entirely from the contributed data only via a latent class analysis. The results show that consensus approaches do yield a classification that is more accurate than that achieved by any individual contributor. Here, the most accurate individual could classify the data with an accuracy of 73.91% while a basic consensus label derived from the data provided by all seven volunteers contributing data was 76.58%. More importantly, the results show that weighting contributions can lead to a statistically significant increase in the overall accuracy to 80.60% by ignoring the contributions from the volunteer adjudged to be the least accurate in labelling.

Motility and β-Lactamases: Occurrences of Antibiotic Resistance in Nosocomial Infections

The widespread use of β-lactam antibiotics has resulted in the global emergence of antibiotic-resistant bacterial strains. Multidrug resistant isolates are now more difficult to treat due to multiple intrinsic and acquired mechanisms of drug resistance that operate simultaneously in a bacterial cell. Motility is associated with virulence that contributes to multidrug resistance. The current analysis has shown that natural pattern of distribution of Ambler (molecular) classes of β-lactamases (A, B, C, D) varied among motile and non-motile nosocomial pathogens. Our results revealed that the relative abundance of class A β-lactamases was highest in bacterial species that are non-motile. However, the relative abundance of class C β-lactamases was mostly same for both motile and non-motile bacterial species. The class D β-lactamases was found highest in bacterial species that are non-motile. However, based upon the total number of sequences checked, the prevalence of class B β-lactamases dominated in pathogens that are motile when compared to other Ambler classes of β-lactamases. Our results imply that occurrence of class B β-lactamases may prove advantageous to motile bacterial species. This may also suggest that the gain of class B β-lactamases genes during the course of their evolution may have contributed to their virulence.

STATIC LIFE-TABLE ANALYSIS OF FALL RATES OF SUBALPINE FIR SNAGS

A conflict exists in managed forests between the maintenance of snags (standing dead trees) for biological diversity and the requirement to remove snags for worker safety. This conflict could be mitigated by the identification of safe classes of snags, those with low rates of fall, that can be easily identified and retained in forest operations. I outline an approach to estimating rates of fall of identifiable decay classes of snags based on static life-table analysis of the current age distribution and relative abundance of classes of snags in a stand, applying the analysis to subalpine fir (Abies lasiocarpa) snags. The two most recent classes of snags, identified by the presence of fine branches and intact bark, showed fall rates of 0.17–0.20%/yr, similar to or lower than live subalpine fir trees. Fall rates increased to 0.70%/yr for the third class of snags, identified by loss of fine branches and cracking of bark, and to 3.79% and 6.16%/yr for the fourth and fifth classes, respectively, identified by ...